论文标题
Duidd：对MIMO无线系统的深度解释的交织检测和解码
DUIDD: Deep-Unfolded Interleaved Detection and Decoding for MIMO Wireless Systems
论文作者
论文摘要
已知迭代检测和解码（IDD）在多Antenna无线系统中实现近容量的性能。我们提出了深度折叠的交错检测和解码（DUIDD），这是一种新的范式，可降低IDD的复杂性，同时达到较低的错误率。 Duidd交织了数据检测器和通道解码器的内部阶段，这加快了收敛并降低复杂性。此外，杜德（Duidd）深入展开，以自动优化算法超参数，软信息交换，消息阻尼和状态转发。我们使用NVIDIA的Sionna链路级模拟器在5G-NEAR多用户MIMO-OFDM无线系统中证明了Duidd的功效，并具有新型的低估性软输入数据检测器，这是一个优化的低密度平价 - 检查器，以及从商业射线射线传播器中通道矢量。我们的结果表明，杜德（Duidd）在块错误率和计算复杂性方面都优于经典IDD。
Iterative detection and decoding (IDD) is known to achieve near-capacity performance in multi-antenna wireless systems. We propose deep-unfolded interleaved detection and decoding (DUIDD), a new paradigm that reduces the complexity of IDD while achieving even lower error rates. DUIDD interleaves the inner stages of the data detector and channel decoder, which expedites convergence and reduces complexity. Furthermore, DUIDD applies deep unfolding to automatically optimize algorithmic hyperparameters, soft-information exchange, message damping, and state forwarding. We demonstrate the efficacy of DUIDD using NVIDIA's Sionna link-level simulator in a 5G-near multi-user MIMO-OFDM wireless system with a novel low-complexity soft-input soft-output data detector, an optimized low-density parity-check decoder, and channel vectors from a commercial ray-tracer. Our results show that DUIDD outperforms classical IDD both in terms of block error rate and computational complexity.
